• 대한물리의학회지
• /
• 제10권4호
• /
• pp.25-31
• /
• 2015

PURPOSE: Previous studies have shown that healthy young adults reduced gait velocity during texting or talking while walking. It was reported that increasing number of pedestrian accidents were related to distract the environmental attention. The purpose of this study was to compare the effects of texting and texting while listening to music on gait parameters. METHODS: Texting and listening to music while walking were assessed in two dual-task condition using 35 healthy young adults. The outcome measurements were assessed in terms of spatiotemporal gait parameters in three walking conditions, namely, comfortable walking speed, walking while texting, and walking while texting and listening to music. To avoid learning effect, subjects were individually blinded to assessment schedule and space. The changes between the three walking conditions were analyzed using repeated measures ANOVA. RESULTS: When comparing the two dual-task conditions with the single-task condition, it was found that dual-task interference was increased in almost gait velocity, cadence, stride length, step time, double limb support, and single limb support. In addition, walking while texting and listening to music condition negatively was affected gait speed, stride length, and step time more than the texting only condition. CONCLUSION: Walking while texting and listening to music as well as waling while texting may decrease pedestrian safety when crossing streets by diverting the person's attention away from the street environment.

• 한국운동역학회지
• /
• 제17권3호
• /
• pp.147-154
• /
• 2007

This study's purpose is to investigate the effects on leg muscle activity caused by perturbation, using a trapdoor system during the support phase of gait for healthy adults (n = 6, height $177.5{\pm}5.5cm$, weight $81.0{\pm}9.5kg$, age $30.0{\pm}3.3yrs$). The trapdoor had the functional ability of causing inversion or eversion. The release time for the trapdoor was specified for two times, 0.3 and 0.5 seconds after heel contact. While altering these variables, EMG was recorded for the leg muscles (rectus femoris, biceps femoris, vastus lateralis, tibialis anterior, gastrocnemius, soleus). The following conclusions were derived. The steptime was longer for the 0.5s eversion than 0.3s inversion condition. So in order to regain stability after the perturbation the unsupporting leg reached forward rapidly. This quick reflex can be observed through the center of pressure (COP) and its rapid change in direction. The gastrocnemius was activated throughout the total experiment. There was a low amount of activity recorded in the rectus femoris, vastus lateralis and tibialis anterior except for the condition of inversion 0.3s. For most of the conditions, the highest average EMG peak values were recorded during the condition of inversion 0.3s. The iEMG patterns were similar for the conditions of inversion 0.3s and eversion 0.3s. To cope with the rapid change in these conditions, the biceps femoris was activated. During the experiment except for the condition of normal gait, the activity of the soleus and gastrocnemius was relatively high. Therefore, to prevent injury from perturbation of the lower leg strengthening of the soleus and gastrocnemius is required. Likewise to prevent injury to the thigh strengthening for the biceps femoris.

• 스마트미디어저널
• /
• 제6권2호
• /
• pp.33-41
• /
• 2017

철도 선로전환기는 열차의 진로를 현재의 궤도에서 다른 궤도로 제어하는 장치이다. 선로전환기의 노후화로 인한 이상 상황은 탈선 등과 같은 심각한 문제를 발생할 수 있기 때문에, 선로전환기의 적절한 교체시기를 결정하는 것은 매우 중요하다. 본 논문에서는 국내 철도 현장에서 획득한 선로전환기의 전류신호로부터 다차원 데이터 큐브를 구성하고 OLAP(On-Line Analytical Processing) 분석을 통하여 체계적으로 "교체가 필요한 데이터"와 "교체 시점이 아닌 데이터" 집합을 정제하여 분류하였다. 또한 선로전환기의 교체시기 탐지 문제를 이진 분류 문제로 해석하여 이진 분류기의 대표적 모델인 SVM(Support Vector Machine)을 탐지기로 설계함으로써 선로전환기의 노후화에 따른 적절한 교체시기를 탐지하는 시스템을 제안한다. 이때, 입력되는 전류 신호를 DWT(Discrete Wavelet Transform)와 PCA(Principal Components Analysis) 기법으로 고차원의 특징벡터 신호를 정보의 손실을 최소화하면서 저차원의 특징벡터로 변환한다. 실제 국내에서 운행 중인 선로전환기의 이상상황 정보가 포함된 대규모의 전류 신호를 이용하여 제안하는 시스템의 성능을 실험적으로 검증한 바 98%를 넘는 탐지 정확도를 확인하였다.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
• /
• pp.1979-1983
• /
• 2011

FRP(Fiber Reinforced Plastic) support insulators for DC(direct current) were developed and their electrical and mechanical characteristics were investigated. Electrical tests were carried out to measure flashover voltages under common use frequency condition. Tensile and bending tests were performed for the mechanical characteristics. The test results showed that FRP support insulators have superior voltage resistances and strengths to porcelain insulators. Field test also is carried out to measure adaptation and to compensate the defect. The test result showed that a new product has no defect in electrical and mechanical.

• Structural Engineering and Mechanics
• /
• 제18권3호
• /
• pp.303-314
• /
• 2004

An artificial neural network (ANN) application is presented for flexural and axial vibration analysis of elastic beams with various support conditions. The first three natural frequencies of beams are obtained using multi layer neural network based back-propagation error learning algorithm. The natural frequencies of beams are calculated for six different boundary conditions via direct solution of governing differential equations of beams and Rayleigh's approximate method. The training of the network has been made using these data only flexural vibration case. The trained neural network, however, had been tested for cantilever beam (C-F), and both end free (F-F) in case the axial vibration, and clamped-clamped (C-C), and Guided-Pinned (G-P) support condition in case the flexural vibrations which were not included in the training set. The results found by using artificial neural network are sufficiently close to the theoretical results. It has been demonstrated that the artificial neural network approach applied in this study is highly successful for the purposes of free vibration analysis of elastic beams.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2006년도 추계학술대회논문집
• /
• pp.401-406
• /
• 2006

This paper presents the fault diagnosis of induction motor based on support vector machine(SVMs). SVMs are well known as intelligent classifier with strong generalization ability. Application SVMs using kernel function is widely used for multi-class classification procedure. In this paper, the algorithm of SVMs will be combined with feature extraction and reduction using component analysis such as independent component analysis, principal component analysis and their kernel(KICA and KPCA). According to the result, component analysis is very useful to extract the useful features and to reduce the dimensionality of features so that the classification procedure in SVM can perform well. Moreover, this method is used to induction motor for faults detection based on vibration and current signals. The results show that this method can well classify and separate each condition of faults in induction motor based on experimental work.

• 한국소음진동공학회논문집
• /
• 제14권12호
• /
• pp.1233-1240
• /
• 2004

Condition monitoring and fault diagnosis of machines are gaining importance in the industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. By comparing the nitration signals of a machine running in normal and faulty conditions, detection of faults like mass unbalance, shaft misalignment and bearing defects is possible. This paper presents a novel approach for applying the fault diagnosis of rotating machinery. To detect multiple faults in rotating machinery, a feature selection method and support vector machine (SVM) based multi-class classifier are constructed and used in the faults diagnosis. The results in experiments prove that fault types can be diagnosed by the above method.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2003년도 추계학술대회 논문집(II)
• /
• pp.454-459
• /
• 2003

The process of determining whether, when, where and how to intervene, of deciding on optimum allocation of resources and minimizing the cost is a very complex problem: different track sections tend to behave differently under the effects of loading; decision-making processes for maintenance work are closely interrelated technically and economically; decision-making for maintenance plans is based on a large quantity of technical and economic information, extensive knowledge and above all experience. For that reason, It is considered very important to develope objective and computer-aided decision-making support system for track maintenance plan. On this paper, we reviewed ECOTRACK system and present the plan of develope decision-making support system for track maintenance appropriate to local condition.

• Journal of Chest Surgery
• /
• 제45권3호
• /
• pp.186-188
• /
• 2012

Status asthmaticus is a rare, fatal condition, especially in children. Sometimes respiratory support is insufficient with a mechanical ventilator or medical therapy for patients with status asthmaticus. In such situations, early extracorporeal membrane oxygenation application is a useful method for treating refractory respiratory failure. We report on a case of a six-year-old, male child who underwent venovenous extracorporeal membrane oxygenation support for refractory status asthmaticus.

• 한국해양공학회:학술대회논문집
• /
• 한국해양공학회 2006년 창립20주년기념 정기학술대회 및 국제워크샵
• /
• pp.46-53
• /
• 2006

This paper presents the fault diagnosis of induction motor based on support vector machine (SVMs). SVMs are well known as intelligent classifier with strong generalization ability. Application SVMs using kernel function is widely used for multi-class classification procedure. In this paper, the algorithm of SVMs will be combined with feature extraction and reduction using component analysis such as independent component analysis, principal component analysis and their kernel (KICA and KPCA). According to the result, component analysis is very useful to extract the useful features and to reduce the dimensionality of features so that the classification procedure in SVM can perform well. Moreover, this method is used to induction motor for faults detection based on vibration and current signals. The results show that this method can well classify and separate each condition of faults in induction motor based on experimental work.